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A comparative experimental study on the collection and analysis of DNA samples from under-fingernail materials
Full text linkFunding agency : Yıldız Technical University Scientific Researc Fund
Grant number : FYL-2020-4072In cases of murder and rape where there is physical contact between the perpetrator and the victim, analysis of the victim's fingernail material is quite valuable. Although it is possible that the foreign DNA detected in the fingernail material does not belong to the perpetrator of the incident, if it does belong to the perpetrator of the incident, it may provide useful findings for solving the incident. Fingernail material collected after the incident often contains mixed DNA. The efficiency of sample collection procedures is of particular importance, as this process may pose some problems in the interpretation of autosomal short tandem repeat analyses used for the identification of the individual or individuals. The aim of this study is to compare three different fingernail material collection procedures (thick-tipped swabbing, thin-tipped swabbing and nail clipping) to determine the most efficient sample collection procedure and to contribute to routine investigations to identify the assailant in forensic cases. In our study, under-fingernail materials was collected from 12 volunteer couples by three different methods. To help compare the efficiency of the three different methods, the profiles obtained were classified based on the number of female and male alleles detected. In the obtained short tandem repeat profiles, while nail clipping yielded 58.3% (n= 7) "High level DNA mixture" as a profile containing 12 or >12 female alleles, 75% (n= 9) of the samples taken with cotton-toothpick swabs (thin-tipped) yielded "Full male profile". In conclusion, our study shows that cotton-toothpick swabs (thin-tipped) are the most efficient method for determining the male DNA profile among three different fingernail material collection procedures. We suggest that using thin-tipped swabs produced in a specific standard, instead of the standard swabs commonly used in routine crime investigations, to identify perpetrators from fingernail material may improve the efficiency of processing nail material and evaluating evidence
Barriers to healthcare access and continuity of care among Ukrainian war refugees in Europe: findings from the RefuHealthAccess study
No full textArticle number : 1516161Introduction: The Russian invasion of Ukraine displaced over 14 million people. By 2024, around 6 million Ukrainian refugees settled in Europe under the EU Temporary Protection Directive, providing permit of residence, work and health care. This influx strained European healthcare systems, particularly in addressing acute injuries. As the stay of refugees in EU countries prolongs, the management of chronic conditions becomes increasingly important. However, there is limited information available about Ukrainian refugees' access to various healthcare services. Aim: The aim of this study was to evaluate perceived accessibility of healthcare services in Europe for Ukrainian war refugees and to identify barriers to healthcare access, in order to inform improvements in healthcare provision. Methods: A cross-sectional online survey was conducted across Europe from July 2023 to April 2024, targeting adult Ukrainian war refugees. Survey explored areas defined as key health care needs. Descriptive, parametric and non-parametric statistical analysis methods were employed in data analysis. Results: Of 659 respondents, 550 (83.4%) were included in the final analysis due to having reported need to use healthcare services in the past year. The most prevalent needs included dental care (82.9%), prescription medication (81.6%), care for acute (78.4%), and chronic conditions (64.0%). Perceived access to care varied across services, with vaccinations rated highest, while chronic condition care rated lowest. Around ¼ of respondents reported that they had to temporarily return to Ukraine for services not available in the countries where they stayed, these being mostly dental and gynaecologic care. The most prevalent barriers reported were long waiting times (64.2%), information barriers (55.5%), and high service costs (49.1%). Discussion: The survey identified several barriers in the access to healthcare system for Ukrainians, particularly for chronic conditions care. Some barriers may be subjective, relating to limited access to information. However, others point to potential shortcomings within national healthcare systems, suggesting areas that require further review and improvement. Conclusions: Addressing language barriers, improving information dissemination, and enhancing chronic condition management were identified as crucial for improving healthcare access for Ukrainian war refugees. Coordinated strategies are needed to support refugees and ensure the sustainability of host healthcare systems. Copyrigh
Efficient Fault Detection in Photovoltaic Systems Using Machine Learning: A Comparative Analysis of Tree-Based Models
No full textConference name : 15th International Conference on Electrical Engineering, ICEENG 2025.
Conference city : Cairo
Conference date : 12 May 2025 - 15 May 2025
Conference code : 209654Using the most recent machine learning techniques, this article examines several defect detection algorithms that may be utilised in photovoltaic (PV) systems. Maintaining energy efficiency and economic stability requires accurate defect detection, which is becoming increasingly important as the use of renewable energy and large-scale photovoltaic systems continue to expand. Faults that are common in photovoltaic systems, such as string, string-to-ground, and string-to-string faults, can have a significant negative influence on production and result in financial losses. The research presents a flaw detection technique that makes use of classifiers such as Decision Tree, Random Forest, XGBoost, Gradient Boosting, and Extra Trees. We used data from a simulated photovoltaic power plant with a capacity of 250 kW. This data included 600 training instances, 50 testing instances, and 30 characteristics. Among the defects that were examined were those that occurred during normal operation (16.67%), string faults (25.5%), string-to-ground faults (24.83%), and string-to-string mistakes (33%). Accuracy, F1 score, recall, precision, and training duration were the aspects that were considered while evaluating the models. Due to the fact that the Decision Tree model earned the maximum accuracy of 95%, an F1-score of 0.949, recall of 0.95, and precision of 0.958, all while requiring just 0.0083 seconds for training, it is an excellent choice for applications that need real-time processing. The next best model was Random Forest, which achieved an accuracy of 88%, an F1-score of 0.879, and a training time of 0.4856 seconds. The accuracies of XGBoost and Gradient Boosting were below average, coming in at 79% and 78%, respectively. Additionally, the training durations for Gradient Boosting were significantly longer, requiring 4.732 seconds. Extra Trees demonstrated the lowest accuracy, with a score of 74%, an F1-score of 0.723, and a training time of 0.3199 seconds
Is age a determinant in cervical cancer screening in women aged 18 to 29?: An observational study
Full text linkArticle number : e42765This study aims to analyze the impact of aging on cervical cancer screening among women aged 20 to 29. Specifically, it examines the occurrence of abnormal histological results and Cervical Intraepithelial Neoplasia (CIN) (+) lesions within these age groups. We retrospectively analyzed women aged 18 to 29 ( 26 age group. Similarly, conization results showed a lower incidence of CIN 3 lesions in women older than 26. Women aged 18 to 25 had a higher likelihood of CIN 3 diagnosis. These findings emphasize the importance of considering age in the diagnosis of CIN (+) lesions during cervical cancer screening
Dynamic Alteration of HALP Score as a Predictor in Patients with Receiving Immunotherapy for Advanced Non-Small Cell Lung Cancer
Full text linkArticle number : 989.Background and Objectives: This study aimed to investigate the prognostic value of the hemoglobin–albumin–lymphocyte–platelet (HALP) score—a marker reflecting both inflammatory and nutritional status—in patients with metastatic non-small cell lung cancer (NSCLC) undergoing immunotherapy. We also sought to determine whether dynamic changes in the HALP score during treatment could predict therapeutic success and help distinguish between pseudoprogression and hyperprogression. Materials and Methods: A retrospective analysis was conducted on 160 patients diagnosed with metastatic NSCLC and treated with immunotherapy at the Ankara Atatürk Sanatorium Training and Research Hospital. Chemotherapy regimens, metastatic sites, baseline and third-month hemograms and biochemistry parameters, and survival data were recorded. Survival outcomes were analyzed using the Kaplan–Meier method with the log-rank test and the Cox proportional hazards regression model using IBM SPSS Statistics. Results: The median overall survival (OS) for the entire cohort was 15 months (95% CI: 11.88–18.12). HALP1 score (p = 0.048), HALP2 score (p = 0.026), and hyperprogression (p < 0.001) were statistically significant predictors of OS. Regarding progression-free survival (PFS), the HALP2 score (p = 0.031), line of immunotherapy (p = 0.046), and hyperprogression (p < 0.001) were found to be significant. When comparing patients with increasing versus decreasing HALP scores, those with increasing HALP scores demonstrated significantly better outcomes for both OS (p = 0.034) and PFS (p = 0.007). Conclusions: In patients with metastatic NSCLC undergoing immunotherapy, the HALP score and its dynamic alterations during treatment appear to be non-invasive, easily calculable biomarkers that may predict both OS and PFS
The Effect of Maternal Attitudes and Depression on Bonding During the Postpartum Period
Full text linkPurpose: Bonding refers to the development of an emotional relationship between a mother and her baby, which forms a strong and continuous bond that provides the baby with a sense of security and plays an important role in its mental well-being throughout life. The objective of this study was to assess the relationship between cognitive distortions, attitudes towards motherhood and postpartum depression, which have not been studied before, as well as to elucidate their impact on the mother-infant bonding process. Patients and Methods: The sample of the study was created between November 2018-June 2019 using the non-discriminatory multiplicity snowball sampling technique through social media. Women with infants aged 0–1 year residing in Turkey were asked to participate in the online survey. A sociodemographic data form, the Edinburgh Postpartum Depression Scale, Attitudes Towards Motherhood Scale (AToM), Postpartum Bonding Questionnaire (PBQ), and Cognitive Distortions Scale (CDS) were applied to the sample via social media. Results: The study sample consisted of 387 women with infants aged 0–1 years, and the rate of impairment bonding was found to be 11.4%. CDS, ATOM and depression scores were significantly higher in the impaired attached group (p < 0.05). The findings indicated that an individual with a psychiatric diagnosis was 2.653 times more likely to exhibit impaired bonding (OR: 2.653, 95% CI: [1.08–6.517]; p = 0.033), and those with a higher AToM score were 1.044 times more likely to display impaired bonding (OR: 1.044, 95% CI: [1.013–1.075]; p = 0.004). Conclusion: The cognitive structure of the mother is associated with impaired mother-baby bonding. Eliminating the mentioned cognitive elements with psychotherapy interventions will be protective in terms of impaired bonding related to psychopathologies and/ or interpersonal relationship problems
Automated Age Estimation from OPG Images and Patient Records Using Deep Feature Extraction and Modified Genetic-Random Forest
Full text linkBackground/Objectives: Dental age estimation is a vital component of forensic science, helping to determine the identity and actual age of an individual. However, its effectiveness is challenged by methodological variability and biological differences between individuals. Therefore, to overcome the drawbacks such as the dependence on manual measurements, requiring a lot of time and effort, and the difficulty of routine clinical application due to large sample sizes, we aimed to automatically estimate tooth age from panoramic radiographs (OPGs) using artificial intelligence (AI) algorithms. Methods: Two-Dimensional Deep Convolutional Neural Network (2D-DCNN) and One-Dimensional Deep Convolutional Neural Network (1D-DCNN) techniques were used to extract features from panoramic radiographs and patient records. To perform age estimation using feature information, Genetic algorithm (GA) and Random Forest algorithm (RF) were modified, combined, and defined as Modified Genetic-Random Forest Algorithm (MG-RF). The performance of the system used in our study was analyzed based on the MSE, MAE, RMSE, and R2 values calculated during the implementation of the code. Results: As a result of the applied algorithms, the MSE value was 0.00027, MAE value was 0.0079, RMSE was 0.0888, and R2 score was 0.999. Conclusions: The findings of our study indicate that the AI-based system employed herein is an effective tool for age detection. Consequently, we propose that this technology could be utilized in forensic sciences in the future
European Oral Research
No full textPurpose The primary objective of this investigation is to evaluate the clinical and radiographic findings of mineral trioxide aggregate (MTA) and Biodentine (BD) as pulpotomy agents in primary molars. Materials and Methods Two hundred primary molars (N=200) were treated with pulpotomy. Clinical and radiographic outcomes, including both successes and failures, were documented throughout a 36-month follow-up period. Statistical analyses were performed using the Fisher Exact, McNemar, and Chi-Square tests. Results No statistically significant differences in success rates were found between the 1-, 3-, 6-, 24-, and 36-month assessments for each material when evaluated independently. However, at the twelfth month, the clinical and radiographic success rates for MTA (98% and 92%, respectively) were significantly higher than those for BD (90% and 80%, respectively) with a p-value of less than 0.05. Conclusion In this study, MTA demonstrated greater success than BD at 36 months. Nevertheless, higher quality randomized controlled trials with longer follow-up periods are necessary to obtain more reliable results
Cybersecurity Strategies for Protecting Big Data in Business Intelligence Systems in Urban Cities
No full textCyberattacks can severely undermine public trust in enterprises, disrupt financial operations, and result in substantial monetary losses. This research investigates the influence of cybersecurity on operational efficiency and profitability in metropolitan areas. Data was gathered from 50 employees in metropolitan areas. The electronic distribution of questionnaires via Google Forms achieved a response rate exceeding 99 %, surpassing previous studies. Data was analyzed utilizing SPSS 26 and structural equation modelling. This study also analyzed the demographics of participants, a distinction not addressed in prior studies. The predominant demographic of the study sample consisted of females aged 25 to 35 who were high school graduates. The study also analyzed the relationship between cybersecurity and other variables using Pearson's correlation analysis. The research indicated that cybersecurity is a significant predictor of operational efficiency and profitability in enterprises located in Misrata. This study is distinctive as it investigated the correlation among all variables influencing Pearson's correlation coefficient, revealing a positive relationship. This study is among the few that examine corporate cybersecurity in Libya. It advocates for the enhancement of detection and response strategies to mitigate emerging cyber threats, thus safeguarding operations and customer dat
Effect of infection control barriers of light curing units on adhesive cementation of glass ceramics to enamel
No full textPurpose: To evaluate the effect of different infection control barriers used with light curing units (LCU) on the shear bond strength (SBS) of glass ceramics with various translucencies and thicknesses during adhesive cementation.
Methods: 60 extracted molar teeth cut in halves mesio-distally to obtain 120 enamel surfaces. Lithium disilicate blocks (GC, Initial Lisi Blocks); 30 High Translucency (HT) 0.5 mm, 30 Low Translucency (LT) 0.5 mm, 30 HT 1.0 mm, 30 LT 1.0 mm discs with 3 mm diameter were produced (n=120). Samples were categorized into three groups according to the infection control barriers (n=40): 1-LCU without barrier, 2-Disposable barrier on LCU (Pinnacle Cure Sleeve), 3-LCU wrapped with stretch film. The SBS test was performed after thermocycling. Failure modes were determined at x20 and classified and statistically analyzed (P< 0.05).
Results: Differences between all the groups were significant (P< 0.001). The highest SBS values were obtained as HT LCU 0.5 mm, LT LCU 0.5 mm, HT Sleeve 0.5 mm and LT Sleeve 0.5 mm, respectively. Highest SBS values were seen in HT LCU 0.5 mm (16.51± 0.68), while LT 1.0 mm stretch (10.76± 1.37) showed the lowest values. Mostly mixed failures occurred in the 0.5 mm sample groups showing higher SBS values.
Clinical significance: While the application of a sleeve on a LCU may slightly reduce the shear bond strength values of glass ceramics, it can still be beneficial for the cementation of these materials as it helps prevent cross-infection